Guest Blogger Brad Barash - Taking the Queasiness Out of Research Reporting

I'm excited to have Brad Barash from Decision Insight in Kansas City as the first guest blogger. Brad and I worked together for a number of years, and he was the creative force behind a video called, "How to Kill a Business." It remains one of the best examples I've ever seen of portraying research insights in a fun and incredibly memorable way using video. So when it comes to expertise in communicating research reports in unique, impactful ways, he knows from where he speaks!

When Mike asked me to write about communicating research results, one word quickly came to mind:

Regurgitation.

What a great word. So vivid. So unmistakable in its connotation.

I cannot think of a better word (unfortunately) to describe the typical research report. Too often, the “writing” in reports is simply regurgitation of the data on the slide (“17% of respondents _____”). That’s not delivering insight. That’s dumping data. (Regurgitating, dumping… may be coming from different places, but the result is the same!)

Our job as researchers and marketers is to tell a story, not report data. We should be writing the column on the sports page, not simply delivering the box scores.

There is a reason most reports don’t feel like a cohesive story. Researchers are too quick to create charts and graphs. Then, the charts and graphs are put in “chronological” order (i.e. question 1 on slide 1, question 2 on slide 2, etc.). When you do this, you are confined to a structure that is rarely conducive to telling the best story.

To go from data dump to story, use what I call the “note card puzzle” approach. First, scour the data, and write every key finding on a separate note card. At this point, it is OK to simply regurgitate the data point onto the card.

Then, physically put together the cards that “fit” together, or those that point to a consistent theme.

From there, come up with no more than 3-4 key themes, or big picture “insights.”

Next, re-sort the note cards across the key insights as follows:

• Support one of the key insights
• Contradict one of the key insights
• Spurious (do not support or contradict any of the key insights)

Ideally, there are few contradictory data points. If they do exist, first find out if they truly contradict the insight. To understand how to sort through meaningful data interpretations, check out this article by Richard McCullough. (This should be required reading for any researcher!)

If there are meaningful contradictions, then the key insights likely need to be revised. Most often, however, you are left with some spurious data points that should be buried in the appendix. And, with the “supporting” data points, you have a structure that makes telling the story simple. Key insight 1 is _____, and here is the data that supports that; key insight 2 is ______, and here is the data that supports that, etc.

One final trick to telling a story: do NOT use statistics or data in your headlines. Quick Example:

• Page 1 - Key Insight: The Jayhawks are a solid pick to win the National Championship this year.
• Page 2 - Headline: They are a veteran team.
  Support charts/graphs: % of upperclassman relative to other contenders
• Page 3 - Headline: They have won big games already this year.
  Support charts/graphs: # of wins vs. ranked teams
• Page 4 - Headline: They are balanced, so they can overcome a poor game by any one player.
  Support charts/graphs: scoring averages of starters relative to other contenders
• Etc.

Here’s hoping this example does not make any non-Jayhawk fans regurgitate! But, notice how there is no statistic in any insight or headline. The data that is reported simply supports the writing. -- Brad Barash